{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "6e0fc110",
   "metadata": {},
   "source": [
    "## Exploratory Data Analysis (EDA) - Introducing lags\n",
    "\n",
    "#### In this notebook we provide a statistical data analysis not solely based on raw data but on their 10 observations slot mentioned in the Challenge Description"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f48a11fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "import sys\n",
    "\n",
    "from pathlib import Path\n",
    "\n",
    "\n",
    "parent = Path(os.path.abspath(\"\")).resolve().parents[0]\n",
    "\n",
    "if parent not in sys.path:\n",
    "    sys.path.insert(0, str(parent))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fe645156",
   "metadata": {},
   "outputs": [],
   "source": [
    "import copy\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "from matplotlib.ticker import FuncFormatter\n",
    "import matplotlib.ticker as ticker\n",
    "import seaborn as sns\n",
    "import colorcet as cc\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a51218ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "from ml.utils.data_utils import read_data, generate_time_lags"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "106e1916",
   "metadata": {},
   "source": [
    "### We read the full dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ef472c4a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = read_data(\"../dataset/full_dataset.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d4879b20",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4192, 6892, 15927)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df.loc[df.District == \"ElBorn\"]), len(df.loc[df.District == \"LesCorts\"]), len(df.loc[df.District == \"PobleSec\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "57913d95",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>down</th>\n",
       "      <th>up</th>\n",
       "      <th>rnti_count</th>\n",
       "      <th>mcs_down</th>\n",
       "      <th>mcs_down_var</th>\n",
       "      <th>mcs_up</th>\n",
       "      <th>mcs_up_var</th>\n",
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       "      <th>rb_down_var</th>\n",
       "      <th>rb_up</th>\n",
       "      <th>rb_up_var</th>\n",
       "      <th>District</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "    <tr>\n",
       "      <th>2018-03-28 15:56:00</th>\n",
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       "      <td>0.000541</td>\n",
       "      <td>3.143298e-08</td>\n",
       "      <td>ElBorn</td>\n",
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       "    <tr>\n",
       "      <th>2018-03-28 15:58:00</th>\n",
       "      <td>209054176.0</td>\n",
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       "      <td>0.000852</td>\n",
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       "      <td>ElBorn</td>\n",
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       "    <tr>\n",
       "      <th>2018-03-28 16:00:00</th>\n",
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       "    <tr>\n",
       "      <th>2018-03-28 16:02:00</th>\n",
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       "      <td>14040.0</td>\n",
       "      <td>15.135400</td>\n",
       "      <td>86.199501</td>\n",
       "      <td>15.714660</td>\n",
       "      <td>77.187462</td>\n",
       "      <td>0.041372</td>\n",
       "      <td>4.532153e-08</td>\n",
       "      <td>0.000925</td>\n",
       "      <td>5.382563e-08</td>\n",
       "      <td>ElBorn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-28 16:04:00</th>\n",
       "      <td>264131088.0</td>\n",
       "      <td>3288816.0</td>\n",
       "      <td>15247.0</td>\n",
       "      <td>15.188944</td>\n",
       "      <td>86.151115</td>\n",
       "      <td>15.414080</td>\n",
       "      <td>69.118561</td>\n",
       "      <td>0.045074</td>\n",
       "      <td>4.655542e-08</td>\n",
       "      <td>0.001021</td>\n",
       "      <td>5.922178e-08</td>\n",
       "      <td>ElBorn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-28 02:24:00</th>\n",
       "      <td>37187568.0</td>\n",
       "      <td>118080.0</td>\n",
       "      <td>2294.0</td>\n",
       "      <td>15.382020</td>\n",
       "      <td>87.171577</td>\n",
       "      <td>16.035715</td>\n",
       "      <td>13.321428</td>\n",
       "      <td>0.006199</td>\n",
       "      <td>4.440420e-08</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>1.754167e-10</td>\n",
       "      <td>PobleSec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-28 02:26:00</th>\n",
       "      <td>33961656.0</td>\n",
       "      <td>69920.0</td>\n",
       "      <td>2155.0</td>\n",
       "      <td>14.984922</td>\n",
       "      <td>83.975639</td>\n",
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       "      <td>4.256897e-08</td>\n",
       "      <td>0.000023</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>PobleSec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-28 02:28:00</th>\n",
       "      <td>40714568.0</td>\n",
       "      <td>154816.0</td>\n",
       "      <td>2519.0</td>\n",
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       "      <td>84.750046</td>\n",
       "      <td>14.323529</td>\n",
       "      <td>16.558823</td>\n",
       "      <td>0.006675</td>\n",
       "      <td>4.471620e-08</td>\n",
       "      <td>0.000051</td>\n",
       "      <td>1.477500e-09</td>\n",
       "      <td>PobleSec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-28 02:30:00</th>\n",
       "      <td>32670760.0</td>\n",
       "      <td>49960.0</td>\n",
       "      <td>2025.0</td>\n",
       "      <td>14.961452</td>\n",
       "      <td>90.345596</td>\n",
       "      <td>16.071428</td>\n",
       "      <td>5.785714</td>\n",
       "      <td>0.005464</td>\n",
       "      <td>4.644022e-08</td>\n",
       "      <td>0.000018</td>\n",
       "      <td>6.337500e-10</td>\n",
       "      <td>PobleSec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-28 02:32:00</th>\n",
       "      <td>61145136.0</td>\n",
       "      <td>304600.0</td>\n",
       "      <td>3758.0</td>\n",
       "      <td>15.221152</td>\n",
       "      <td>86.887466</td>\n",
       "      <td>16.713333</td>\n",
       "      <td>25.465555</td>\n",
       "      <td>0.010337</td>\n",
       "      <td>4.368096e-08</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>4.197597e-09</td>\n",
       "      <td>PobleSec</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>27011 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            down         up  rnti_count   mcs_down  \\\n",
       "time                                                                 \n",
       "2018-03-28 15:56:00  174876896.0  1856888.0     10229.0  15.332298   \n",
       "2018-03-28 15:58:00  209054176.0  2866200.0     12223.0  15.116846   \n",
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       "2018-03-28 16:02:00  241515680.0  2991152.0     14040.0  15.135400   \n",
       "2018-03-28 16:04:00  264131088.0  3288816.0     15247.0  15.188944   \n",
       "...                          ...        ...         ...        ...   \n",
       "2018-02-28 02:24:00   37187568.0   118080.0      2294.0  15.382020   \n",
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       "2018-02-28 02:32:00   61145136.0   304600.0      3758.0  15.221152   \n",
       "\n",
       "                     mcs_down_var     mcs_up  mcs_up_var   rb_down  \\\n",
       "time                                                                 \n",
       "2018-03-28 15:56:00     87.157692  14.981497   49.989483  0.029681   \n",
       "2018-03-28 15:58:00     87.192169  16.432613   62.494671  0.035971   \n",
       "2018-03-28 16:00:00     87.227959  15.885238   63.087006  0.032750   \n",
       "2018-03-28 16:02:00     86.199501  15.714660   77.187462  0.041372   \n",
       "2018-03-28 16:04:00     86.151115  15.414080   69.118561  0.045074   \n",
       "...                           ...        ...         ...       ...   \n",
       "2018-02-28 02:24:00     87.171577  16.035715   13.321428  0.006199   \n",
       "2018-02-28 02:26:00     83.975639  18.900000    0.000000  0.005610   \n",
       "2018-02-28 02:28:00     84.750046  14.323529   16.558823  0.006675   \n",
       "2018-02-28 02:30:00     90.345596  16.071428    5.785714  0.005464   \n",
       "2018-02-28 02:32:00     86.887466  16.713333   25.465555  0.010337   \n",
       "\n",
       "                      rb_down_var     rb_up     rb_up_var  District  \n",
       "time                                                                 \n",
       "2018-03-28 15:56:00  4.497698e-08  0.000541  3.143298e-08    ElBorn  \n",
       "2018-03-28 15:58:00  4.615535e-08  0.000852  4.439640e-08    ElBorn  \n",
       "2018-03-28 16:00:00  4.646104e-08  0.000607  2.993595e-08    ElBorn  \n",
       "2018-03-28 16:02:00  4.532153e-08  0.000925  5.382563e-08    ElBorn  \n",
       "2018-03-28 16:04:00  4.655542e-08  0.001021  5.922178e-08    ElBorn  \n",
       "...                           ...       ...           ...       ...  \n",
       "2018-02-28 02:24:00  4.440420e-08  0.000030  1.754167e-10  PobleSec  \n",
       "2018-02-28 02:26:00  4.256897e-08  0.000023  0.000000e+00  PobleSec  \n",
       "2018-02-28 02:28:00  4.471620e-08  0.000051  1.477500e-09  PobleSec  \n",
       "2018-02-28 02:30:00  4.644022e-08  0.000018  6.337500e-10  PobleSec  \n",
       "2018-02-28 02:32:00  4.368096e-08  0.000095  4.197597e-09  PobleSec  \n",
       "\n",
       "[27011 rows x 12 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7226e243",
   "metadata": {},
   "source": [
    "### We generate data points that include 10 observations to be used as our prediction materials"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a956f096",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_lags_X = generate_time_lags(df, 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ecefc828",
   "metadata": {},
   "outputs": [
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       "      <th>2018-03-28 16:16:00</th>\n",
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       "      <th>2018-03-28 16:18:00</th>\n",
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       "      <td>15.116846</td>\n",
       "      <td>12223.0</td>\n",
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       "      <td>...</td>\n",
       "      <td>4.562575e-08</td>\n",
       "      <td>0.035865</td>\n",
       "      <td>58.438049</td>\n",
       "      <td>15.492438</td>\n",
       "      <td>86.273674</td>\n",
       "      <td>15.225310</td>\n",
       "      <td>12238.0</td>\n",
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       "      <th>2018-03-28 16:20:00</th>\n",
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       "      <td>63.087006</td>\n",
       "      <td>15.885238</td>\n",
       "      <td>87.227959</td>\n",
       "      <td>15.215739</td>\n",
       "      <td>11152.0</td>\n",
       "      <td>1935360.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4.634120e-08</td>\n",
       "      <td>0.035230</td>\n",
       "      <td>58.172825</td>\n",
       "      <td>13.977254</td>\n",
       "      <td>87.437515</td>\n",
       "      <td>15.197440</td>\n",
       "      <td>12020.0</td>\n",
       "      <td>2012688.0</td>\n",
       "      <td>205107312.0</td>\n",
       "      <td>ElBorn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-28 16:22:00</th>\n",
       "      <td>5.382563e-08</td>\n",
       "      <td>0.000925</td>\n",
       "      <td>4.532153e-08</td>\n",
       "      <td>0.041372</td>\n",
       "      <td>77.187462</td>\n",
       "      <td>15.714660</td>\n",
       "      <td>86.199501</td>\n",
       "      <td>15.135400</td>\n",
       "      <td>14040.0</td>\n",
       "      <td>2991152.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4.689734e-08</td>\n",
       "      <td>0.042154</td>\n",
       "      <td>75.962418</td>\n",
       "      <td>15.346758</td>\n",
       "      <td>88.413483</td>\n",
       "      <td>15.160942</td>\n",
       "      <td>14098.0</td>\n",
       "      <td>3320616.0</td>\n",
       "      <td>244770944.0</td>\n",
       "      <td>ElBorn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-28 16:24:00</th>\n",
       "      <td>5.922178e-08</td>\n",
       "      <td>0.001021</td>\n",
       "      <td>4.655542e-08</td>\n",
       "      <td>0.045074</td>\n",
       "      <td>69.118561</td>\n",
       "      <td>15.414080</td>\n",
       "      <td>86.151115</td>\n",
       "      <td>15.188944</td>\n",
       "      <td>15247.0</td>\n",
       "      <td>3288816.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4.516392e-08</td>\n",
       "      <td>0.029265</td>\n",
       "      <td>64.505157</td>\n",
       "      <td>14.037872</td>\n",
       "      <td>86.916840</td>\n",
       "      <td>15.181100</td>\n",
       "      <td>10168.0</td>\n",
       "      <td>1748160.0</td>\n",
       "      <td>171757376.0</td>\n",
       "      <td>ElBorn</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 111 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     rb_up_var_lag-10  rb_up_lag-10  rb_down_var_lag-10  \\\n",
       "time                                                                      \n",
       "2018-03-28 16:16:00      3.143298e-08      0.000541        4.497698e-08   \n",
       "2018-03-28 16:18:00      4.439640e-08      0.000852        4.615535e-08   \n",
       "2018-03-28 16:20:00      2.993595e-08      0.000607        4.646104e-08   \n",
       "2018-03-28 16:22:00      5.382563e-08      0.000925        4.532153e-08   \n",
       "2018-03-28 16:24:00      5.922178e-08      0.001021        4.655542e-08   \n",
       "\n",
       "                     rb_down_lag-10  mcs_up_var_lag-10  mcs_up_lag-10  \\\n",
       "time                                                                    \n",
       "2018-03-28 16:16:00        0.029681          49.989483      14.981497   \n",
       "2018-03-28 16:18:00        0.035971          62.494671      16.432613   \n",
       "2018-03-28 16:20:00        0.032750          63.087006      15.885238   \n",
       "2018-03-28 16:22:00        0.041372          77.187462      15.714660   \n",
       "2018-03-28 16:24:00        0.045074          69.118561      15.414080   \n",
       "\n",
       "                     mcs_down_var_lag-10  mcs_down_lag-10  rnti_count_lag-10  \\\n",
       "time                                                                           \n",
       "2018-03-28 16:16:00            87.157692        15.332298            10229.0   \n",
       "2018-03-28 16:18:00            87.192169        15.116846            12223.0   \n",
       "2018-03-28 16:20:00            87.227959        15.215739            11152.0   \n",
       "2018-03-28 16:22:00            86.199501        15.135400            14040.0   \n",
       "2018-03-28 16:24:00            86.151115        15.188944            15247.0   \n",
       "\n",
       "                     up_lag-10  ...  rb_down_var_lag-1  rb_down_lag-1  \\\n",
       "time                            ...                                     \n",
       "2018-03-28 16:16:00  1856888.0  ...       4.711435e-08       0.036078   \n",
       "2018-03-28 16:18:00  2866200.0  ...       4.562575e-08       0.035865   \n",
       "2018-03-28 16:20:00  1935360.0  ...       4.634120e-08       0.035230   \n",
       "2018-03-28 16:22:00  2991152.0  ...       4.689734e-08       0.042154   \n",
       "2018-03-28 16:24:00  3288816.0  ...       4.516392e-08       0.029265   \n",
       "\n",
       "                     mcs_up_var_lag-1  mcs_up_lag-1  mcs_down_var_lag-1  \\\n",
       "time                                                                      \n",
       "2018-03-28 16:16:00         56.133144     14.842332           86.958221   \n",
       "2018-03-28 16:18:00         58.438049     15.492438           86.273674   \n",
       "2018-03-28 16:20:00         58.172825     13.977254           87.437515   \n",
       "2018-03-28 16:22:00         75.962418     15.346758           88.413483   \n",
       "2018-03-28 16:24:00         64.505157     14.037872           86.916840   \n",
       "\n",
       "                     mcs_down_lag-1  rnti_count_lag-1   up_lag-1   down_lag-1  \\\n",
       "time                                                                            \n",
       "2018-03-28 16:16:00       15.146159           12303.0  2193936.0  209997312.0   \n",
       "2018-03-28 16:18:00       15.225310           12238.0  2551856.0  209190704.0   \n",
       "2018-03-28 16:20:00       15.197440           12020.0  2012688.0  205107312.0   \n",
       "2018-03-28 16:22:00       15.160942           14098.0  3320616.0  244770944.0   \n",
       "2018-03-28 16:24:00       15.181100           10168.0  1748160.0  171757376.0   \n",
       "\n",
       "                     District  \n",
       "time                           \n",
       "2018-03-28 16:16:00    ElBorn  \n",
       "2018-03-28 16:18:00    ElBorn  \n",
       "2018-03-28 16:20:00    ElBorn  \n",
       "2018-03-28 16:22:00    ElBorn  \n",
       "2018-03-28 16:24:00    ElBorn  \n",
       "\n",
       "[5 rows x 111 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lags_X.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "232901b3",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_lags_y = generate_time_lags(df, 10, is_y=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "20f49a01",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>down</th>\n",
       "      <th>up</th>\n",
       "      <th>rnti_count</th>\n",
       "      <th>mcs_down</th>\n",
       "      <th>mcs_down_var</th>\n",
       "      <th>mcs_up</th>\n",
       "      <th>mcs_up_var</th>\n",
       "      <th>rb_down</th>\n",
       "      <th>rb_down_var</th>\n",
       "      <th>rb_up</th>\n",
       "      <th>rb_up_var</th>\n",
       "      <th>District</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-03-28 16:16:00</th>\n",
       "      <td>209190704.0</td>\n",
       "      <td>2551856.0</td>\n",
       "      <td>12238.0</td>\n",
       "      <td>15.225310</td>\n",
       "      <td>86.273674</td>\n",
       "      <td>15.492438</td>\n",
       "      <td>58.438049</td>\n",
       "      <td>0.035865</td>\n",
       "      <td>4.562575e-08</td>\n",
       "      <td>0.000768</td>\n",
       "      <td>3.666732e-08</td>\n",
       "      <td>ElBorn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-28 16:18:00</th>\n",
       "      <td>205107312.0</td>\n",
       "      <td>2012688.0</td>\n",
       "      <td>12020.0</td>\n",
       "      <td>15.197440</td>\n",
       "      <td>87.437515</td>\n",
       "      <td>13.977254</td>\n",
       "      <td>58.172825</td>\n",
       "      <td>0.035230</td>\n",
       "      <td>4.634120e-08</td>\n",
       "      <td>0.000670</td>\n",
       "      <td>4.100988e-08</td>\n",
       "      <td>ElBorn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-28 16:20:00</th>\n",
       "      <td>244770944.0</td>\n",
       "      <td>3320616.0</td>\n",
       "      <td>14098.0</td>\n",
       "      <td>15.160942</td>\n",
       "      <td>88.413483</td>\n",
       "      <td>15.346758</td>\n",
       "      <td>75.962418</td>\n",
       "      <td>0.042154</td>\n",
       "      <td>4.689734e-08</td>\n",
       "      <td>0.001008</td>\n",
       "      <td>4.247607e-08</td>\n",
       "      <td>ElBorn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-28 16:22:00</th>\n",
       "      <td>171757376.0</td>\n",
       "      <td>1748160.0</td>\n",
       "      <td>10168.0</td>\n",
       "      <td>15.181100</td>\n",
       "      <td>86.916840</td>\n",
       "      <td>14.037872</td>\n",
       "      <td>64.505157</td>\n",
       "      <td>0.029265</td>\n",
       "      <td>4.516392e-08</td>\n",
       "      <td>0.000598</td>\n",
       "      <td>3.568987e-08</td>\n",
       "      <td>ElBorn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-28 16:24:00</th>\n",
       "      <td>235021312.0</td>\n",
       "      <td>2729104.0</td>\n",
       "      <td>13703.0</td>\n",
       "      <td>15.095089</td>\n",
       "      <td>87.506920</td>\n",
       "      <td>15.364646</td>\n",
       "      <td>60.214905</td>\n",
       "      <td>0.040206</td>\n",
       "      <td>4.523085e-08</td>\n",
       "      <td>0.000859</td>\n",
       "      <td>4.625785e-08</td>\n",
       "      <td>ElBorn</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            down         up  rnti_count   mcs_down  \\\n",
       "time                                                                 \n",
       "2018-03-28 16:16:00  209190704.0  2551856.0     12238.0  15.225310   \n",
       "2018-03-28 16:18:00  205107312.0  2012688.0     12020.0  15.197440   \n",
       "2018-03-28 16:20:00  244770944.0  3320616.0     14098.0  15.160942   \n",
       "2018-03-28 16:22:00  171757376.0  1748160.0     10168.0  15.181100   \n",
       "2018-03-28 16:24:00  235021312.0  2729104.0     13703.0  15.095089   \n",
       "\n",
       "                     mcs_down_var     mcs_up  mcs_up_var   rb_down  \\\n",
       "time                                                                 \n",
       "2018-03-28 16:16:00     86.273674  15.492438   58.438049  0.035865   \n",
       "2018-03-28 16:18:00     87.437515  13.977254   58.172825  0.035230   \n",
       "2018-03-28 16:20:00     88.413483  15.346758   75.962418  0.042154   \n",
       "2018-03-28 16:22:00     86.916840  14.037872   64.505157  0.029265   \n",
       "2018-03-28 16:24:00     87.506920  15.364646   60.214905  0.040206   \n",
       "\n",
       "                      rb_down_var     rb_up     rb_up_var District  \n",
       "time                                                                \n",
       "2018-03-28 16:16:00  4.562575e-08  0.000768  3.666732e-08   ElBorn  \n",
       "2018-03-28 16:18:00  4.634120e-08  0.000670  4.100988e-08   ElBorn  \n",
       "2018-03-28 16:20:00  4.689734e-08  0.001008  4.247607e-08   ElBorn  \n",
       "2018-03-28 16:22:00  4.516392e-08  0.000598  3.568987e-08   ElBorn  \n",
       "2018-03-28 16:24:00  4.523085e-08  0.000859  4.625785e-08   ElBorn  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lags_y.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "16639c5c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(26981, 26981)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_lags_X), len(df_lags_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "851b32a6",
   "metadata": {},
   "source": [
    "### Printing scatter plots for all the new generated time lags and exery base station."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "3ebb1531",
   "metadata": {},
   "outputs": [],
   "source": [
    "def scatter_plot(df, x_axis, y_axis, district):\n",
    "    fig, ax = plt.subplots(figsize=(10,6))\n",
    "    ax.ticklabel_format(style='plain')\n",
    "\n",
    "    sns.scatterplot(x=df[x_axis], y=df[y_axis])\n",
    "\n",
    "    ax.set_title(district + ' '+ x_axis + ' per ' + y_axis, fontsize = 15, loc='center')\n",
    "    ax.set_ylabel(y_axis, fontsize = 13)\n",
    "    ax.set_xlabel(x_axis, fontsize = 13)\n",
    "    plt.tick_params(axis='x', which='major', labelsize=12)\n",
    "    plt.tick_params(axis='y', which='major', labelsize=10)\n",
    "    ax.yaxis.tick_left() # where the y axis marks will be\n",
    "    plt.yticks(rotation=30)\n",
    "    plt.show()\n",
    "    plt.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f7a81a59",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for district in df_lags_y.District.unique():\n",
    "    tmp = df_lags_y.loc[df_lags_y.District == district]\n",
    "    scatter_plot(tmp, \"down\", \"up\", district)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eab34043",
   "metadata": {},
   "source": [
    "### Printing continuous time series for every base station"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "30b8e81d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def sci_format(x,lim):\n",
    "    return '{:.1e}'.format(x)\n",
    "\n",
    "def distribution_plot(df, x_axis, district, bins=None):\n",
    "    major_formatter = FuncFormatter(sci_format)\n",
    "    fig, ax = plt.subplots(figsize=(10,6))\n",
    "    \n",
    "    sns.histplot(df[x_axis], kde=True, \n",
    "                 bins=bins, alpha=.4, edgecolor=(1, 1, 1, .4),\n",
    "                 stat=\"count\", kde_kws=dict(cut=3),\n",
    "                )\n",
    "\n",
    "    ax.set_xlabel(\"Uplink\")\n",
    "    ax.xaxis.set_major_formatter(ticker.ScalarFormatter(useMathText=True))\n",
    "    ax.yaxis.tick_left() \n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "    plt.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "4fe71618",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for district in df_lags_y.District.unique():\n",
    "    tmp = df_lags_y.loc[df_lags_y.District == district]\n",
    "    distribution_plot(tmp, \"up\", district=district, bins='auto')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6724225c",
   "metadata": {},
   "source": [
    "### A closer look to every base station by cutting off some extreme outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "2785e3a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tmp_df = copy.deepcopy(df_lags_y)\n",
    "tmp_df = tmp_df.loc[tmp_df.up <= 10000000]\n",
    "for district in df_lags_y.District.unique():\n",
    "    tmp = tmp_df.loc[tmp_df.District == district]\n",
    "    distribution_plot(tmp, \"up\", district=district, bins='auto')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41512d75",
   "metadata": {},
   "source": [
    "### Printing useful statistics about skewness, kurtosis for every base station dataset "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "9eaa8e4e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_stats(df, col, district):\n",
    "    print(f\"\\tSkewness [{col}]: {df[col].skew()}\")\n",
    "    print(f\"\\tKurtosis: [{col}]: {df[col].kurt()}\")\n",
    "    print(f\"\\tMean: {df[col].mean()}, Median: {df[col].median()}, Mode: {df[col].mode().values[0]}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "1da0d3c4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Area: ElBorn\n",
      "\tSkewness [up]: 8.326245307922363\n",
      "\tKurtosis: [up]: 132.0775909423828\n",
      "\tMean: 10558638.0, Median: 2032372.0, Mode: 0.0\n",
      "\tSkewness [down]: 2.3513245582580566\n",
      "\tKurtosis: [down]: 5.828850269317627\n",
      "\tMean: 230499040.0, Median: 179385728.0, Mode: 184427232.0\n",
      "\n",
      "\n",
      "Area: LesCorts\n",
      "\tSkewness [up]: 12.292612075805664\n",
      "\tKurtosis: [up]: 321.1800842285156\n",
      "\tMean: 9749587.0, Median: 1237928.0, Mode: 0.0\n",
      "\tSkewness [down]: 0.4803575873374939\n",
      "\tKurtosis: [down]: -0.5704779028892517\n",
      "\tMean: 76088096.0, Median: 68478856.0, Mode: 0.0\n",
      "\n",
      "\n",
      "Area: PobleSec\n",
      "\tSkewness [up]: 8.033005714416504\n",
      "\tKurtosis: [up]: 101.8520736694336\n",
      "\tMean: 12136891.0, Median: 933440.0, Mode: 0.0\n",
      "\tSkewness [down]: 3.5666236877441406\n",
      "\tKurtosis: [down]: 23.846277236938477\n",
      "\tMean: 134151608.0, Median: 102707056.0, Mode: 95205104.0\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for district in df_lags_y.District.unique():\n",
    "    tmp = df_lags_y.loc[df_lags_y.District == district]\n",
    "    print(\"Area:\", district)\n",
    "    get_stats(tmp, \"up\", district=district)\n",
    "    get_stats(tmp, \"down\", district=district)\n",
    "    print(\"\\n\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.9.10 64-bit",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
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